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salesforce unified knowledge
23May

Unified Knowledge to Salesforce Service Agents

Salesforce Introduces Unified Knowledge to Enhance Service Agent Intelligence Salesforce has unveiled Unified Knowledge, a new solution designed to enrich service agents’ ability to resolve customer inquiries. By aggregating information from third-party sources and integrating it into Salesforce, Unified Knowledge complements the data already available in Salesforce’s Data Cloud, creating a more comprehensive knowledge base for service agents. Within Salesforce Service Cloud, Einstein for Service leverages AI to provide service agents with real-time information when addressing customer queries. Previously, this information was drawn from Data Cloud. Now, with Unified Knowledge, data from sources such as SharePoint, Confluence, Google Drive, and brand websites is incorporated, further enhancing the breadth of information available to agents. Expanding Beyond Service Cloud While Service Cloud is the primary use case for Unified Knowledge, the solution is also designed to integrate with other Salesforce platforms, including Sales Cloud, Field Service, Health Cloud, and Financial Services Cloud. Developed in collaboration with Zoomin Software, Unified Knowledge allows for greater cross-platform data accessibility and more efficient workflows across various service touchpoints. Why It Matters While the exact reasoning behind Salesforce’s decision to create a separate data channel for Unified Knowledge, rather than consolidating everything into Data Cloud, remains somewhat unclear, the broader availability of data to service agents could enhance service quality and efficiency. At its core, Unified Knowledge uses generative AI to provide dynamic, context-aware responses to agent and customer queries. Key features of the solution include: With these advancements, Unified Knowledge brings generative AI capabilities into the hands of service agents and workers, allowing for quicker, more accurate decision-making and enhanced customer interactions. The Unified Knowledge feature offers significant potential in revolutionizing how companies provide customer support by improving access to critical data from a wide array of sources, ultimately leading to more informed, efficient, and personalized service. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 23, 2024in Data, Generative AI, Google, Salesforce, Salesforce Service Cloud, Unified Knowledge
Salesforce Commerce Cloud and Einstein Copilot Capabilities
23May

Salesforce Commerce Cloud and Einstein Copilot Capabilities

Salesforce Enhances Commerce Cloud and Einstein Copilot Salesforce has announced a double whammy of upgrades to its Commerce Cloud and Einstein Copilot solutions, aiming to supercharge customer service and experience offerings for merchants. And yes, they’re pulling out all the stops – think of it as giving your online store a superhero cape and a sidekick with a PhD in customer satisfaction. Salesforce Commerce Cloud and Einstein Copilot Capabilities. Enhancements to Commerce Cloud Commerce Cloud is getting three major innovations designed to help businesses create more sophisticated commerce sites, boost personalization, and drive revenue growth. Salesforce promises to tackle rising customer expectations by providing a seamless, integrated experience across all channels. In other words, they’re turning your website into a mind-reading wizard, minus the beard and wand. But probably wearing a cool purple cape with stars. According to Michael Affronti, GM and SVP of Commerce Cloud, these new features will enable Salesforce’s customers to deliver superior shopping experiences: “Commerce companies are looking to architect high-caliber ecommerce sites that can swiftly adapt to changing customer expectations and continue to foster strong customer relationships. With the combined power of data, AI, and CRM, Commerce Cloud gives brands the choice of the right tool so they can build superior shopping experiences their way.” New Commerce Cloud Capabilities Einstein Copilot Advancements Salesforce is pulling out the big AI guns, leveraging generative AI (GenAI) to enhance Einstein Copilot with new marketing and merchandising capabilities alongside its traditional sales and service functions. It’s like your old assistant got a brain transplant and now has the IQ of Einstein, the charm of James Bond, and the work ethic of a coffee-fueled startup founder. Ariel Kelman, President and CMO of Salesforce, emphasized the importance of these advancements: “Marketing and commerce leaders need a trusted advisor to help them tap into the promise of generative AI. With the Einstein 1 Platform we’re giving organizations the power to unify all of their data on one trusted platform. This is the key to getting results from generative AI that are actually useful in driving your business forward.” Key Features of Einstein 1 for Marketing and Commerce Expanding Partnerships and Enhancing AI and Data Offerings In addition to these product enhancements, Salesforce has expanded its partnership with IBM to improve AI and data offerings. The collaboration aims to merge IBM’s watsonx.ai platform with Salesforce’s Einstein 1 software, providing customers with the ability to make data-driven decisions and access actions directly within their workflows. It’s like pairing up Batman and Superman to fight the evil forces of inefficiency and bad data. The partnership includes bidirectional data integration, flexible large language models (LLMs), prebuilt CRM solutions, and a focus on responsible AI development. IBM will also join Salesforce’s Zero Copy Partner Network, ensuring that data moves as smoothly as butter on hot toast. Salesforce Commerce Cloud and Einstein Copilot Capabilities These enhancements and partnerships underline Salesforce’s commitment to providing innovative solutions that enhance customer experiences and drive business growth, all while making sure your digital commerce experience is smoother than a jazz saxophone solo. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 23, 2024in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Commerce Cloud
Service Cloud Digital Engagement
23May

Service Cloud Digital Engagement

Salesforce Enhances Service Cloud Digital Engagement for Unified Customer Interactions Salesforce has unveiled new enhancements to Service Cloud Digital Engagement, aimed at unifying unstructured conversational data from various digital channels, departments, and devices within a single platform. Built on the Einstein 1 Platform, these enhancements enable service leaders to gain a more holistic view of customers, enhancing the value delivered in every interaction. Importance of Enhancements Detailed Enhancements Service Cloud Digital Engagement is designed to deliver seamless, personalized conversational experiences across channels at scale. By connecting to Salesforce Data Cloud, which unifies structured and unstructured enterprise and customer data, companies can engage in more meaningful conversations. Key enhancements include: With Service Cloud built on the Einstein 1 Platform, companies can integrate sales, service, and marketing data into one platform, facilitating more relevant customer experiences and driving business growth. Salesforce’s Perspective Kishan Chetan, EVP & GM of Service Cloud, commented, “As customers interact with companies across more touch points and channels, they are looking for more personalization and a higher-touch experience. With Service Cloud built on the Einstein 1 Platform, companies can bring in sales, service, and marketing data on one platform to deliver more relevant customer experiences and drive business growth.” Customer Reactions Olivia Boles, Director of Operations Projects at PenFed, said, “Being able to see all the communication — chat transcripts, emails, phone calls — on the member’s profile page has totally transformed the agent and member experiences.” Availability Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 23, 2024in Data, Einstein 1 Platform, Enterprise, Salesforce, Salesforce Data Cloud
Generative AI and Service Cloud
23May

Generative AI and Service Cloud

Salesforce Service Cloud users are set to receive more Einstein 1 generative AI tools in June and October. A key development is the expansion of automated customer conversations across more sales and marketing platforms. Generative AI and Service Cloud family of tools is growing. This insight aims to uncover the numerous use cases of generative AI in the modern contact center. We’ll help you understand how generative AI can fast track your contact center’s efficiency, improve data analysis capabilities, streamline QA and coaching processes, and make customers’ experiences better. Today, Salesforce launched Unified Conversations for WhatsApp, which automates bot responses to customer inquiries related to targeted marketing messages on the popular messaging app. Additionally, Salesforce plans to extend support to Line, a messaging app popular in Japan, later this year. These services are built on Salesforce’s Einstein 1 generative AI platform. The platform’s bots aggregate structured and unstructured CRM, product, service, and other data through Salesforce Data Cloud to generate personalized responses. These new features enable conversations to be routed to the digital channels where a Salesforce user’s customers are the most active. And to move omnichannel as customers needs change. Salesforce is also introducing a “bring your own channel” connector to support digital channels not natively covered by the platform. Current examples might include TikTok, Discord, and South Korea’s KakaoTalk, according to Ryan Nichols, Chief Product Officer for Salesforce Service Cloud. Generative AI and Service Cloud “It’s about getting data from all your conversations with customers from Service Cloud into Data Cloud and using that to not just deliver excellent customer service, but also grow your business,” Nichols said. Salesforce Einstein Conversation Mining, a Service Cloud feature currently in beta, aggregates conversations across customer channels to surface insights on the topics customers need help with. This aims to turn inbound customer service from a cost center into a revenue center, a goal long pursued at conferences like Dreamforce and ICMI. This massive change drives more than revenue, it drives ROI. Performance metrics such as time-to-answer and hold-time reduction have traditionally pressured agents to minimize call duration to retain their jobs. Now Salesforce is going to help them. While some skeptics question if generative AI can achieve this ambitious goal, Constellation Research analyst Liz Miller suggests it might be possible. Having previously managed a contact center herself, Miller recognizes the transformative potential of generative AI. With the aid of data, bots, and copilot counterparts assisting humans, agents could save time and access the right information to upsell customers during service engagements. Here are some of the ways Generative AI will change customer service forever. 1. Monitor and Ensure Compliance Maintaining compliance is crucial for fostering customer trust, preserving a positive brand image, and avoiding hefty privacy and compliance fines. In a contact center, compliance mistakes can quickly escalate into costly lawsuits and revenue losses. Generative AI allows your compliance team to proactively manage compliance by quickly identifying trends and addressing issues in real time. Instead of waiting for a compliance issue to escalate, you can fine-tune your AI model to provide compliance insights whenever necessary. For instance, you can ask: This approach offers more comprehensive insights than scorecards, which often lack context and accuracy. Generative AI’s analytical capabilities provide actionable insights to improve compliance across your contact center. 2. Get Insights About Your Call Center Performance at a Glance Generative AI language models make it easier than ever to gain insights into your contact center’s performance. Simply ask the model for the information you need. For example, you can inquire about the real-time average handling time (AHT) by asking, “What is the average handling time today?” But that’s just the beginning. With an advanced language model, you can compare metrics across different quarters or generate ideas for coaching plans by asking for each agent‘s strengths and weaknesses and suggestions for improvement. 3. Automate Post-Call Work Generative AI assistants can act as real-time notetakers, summarizing 100% of calls and freeing agents from manual note-taking. This automation makes after-call work effortless, generating comprehensive and compliant notes with a single click. 4. Capture Coachable Moments Easily Incorporating real-world coachable moments into your sessions is essential for tangible performance improvements. Generative AI can identify areas where agents typically struggle without requiring hours of call listening and note-checking. Traditional methods mean compromising on the specificity of coaching due to time constraints, especially when managing large teams. Generative AI solutions, however, enable call center managers to obtain detailed insights about each agent’s performance quickly. This allows for personalized coaching plans that address individual shortcomings efficiently. You can ask: 5. Improve Decision Making With Efficient Root-Cause Analysis Effective decision-making can transform your contact center. However, many managers struggle to identify the root causes of performance issues. Generative AI algorithms can analyze vast amounts of data and customer interactions, uncovering patterns and trends in customer and agent behavior. These insights help pinpoint the issues most impacting performance and customer satisfaction, allowing you to make informed decisions. The process is nearly fully automated, freeing your team from time-consuming data collection tasks. 6. Reduce Manual Work and Focus on Improvement Improving contact center performance requires extensive data, which is resource-intensive to collect manually. Generative AI simplifies this by analyzing customer interactions and providing actionable insights on demand. This saves time and money, allowing you to focus on improvements that deliver a higher ROI. 7. Scale What Works Discovering and scaling best practices is essential for team-wide success. Generative AI and Natural Language Processing (NLP) models can analyze customer interactions to identify effective strategies and coaching opportunities. For example, if a representative handles challenging situations well, AI can generate tips for other team members based on these successful interactions. Generative AI can identify top-performing agents and analyze their calls to extract best practices, providing a more comprehensive approach than focusing on a single agent. Queries you might use include: 8. Generate Agent Scripts Generative AI enables you to draft and fine-tune agent scripts for various customer interactions. Instead of relying

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May 23, 2024in Generative AI, Salesforce Data Cloud, Salesforce Einstein, Salesforce Service Cloud
Using Salesforce for Project Management
23May

Using Salesforce for Project Management

Using Salesforce for Project Management Tasks Leverage the power of SFDC to streamline your project management process and enhance client satisfaction. With Salesforce’s array of features, you can efficiently track project milestones and foster effective communication within your project team. Successful project outcomes hinge on effective project management, ensuring alignment among stakeholders, setting realistic expectations, and addressing risks. This entails meticulous planning, clear cost expectations, and well-defined deliverables and milestones. By establishing structured processes and roles within the project team, you can increase the likelihood of meeting objectives, maintain quality standards, and enhance client satisfaction. Facilitate Project Management Incorporating project management into your Salesforce solution offers a holistic view of the client lifecycle, from initial opportunity to implementation and beyond. Salesforce enables seamless communication among team members and facilitates project oversight, ensuring timely delivery of client requirements. Additionally, it identifies potential sales opportunities, further enhancing client relationships and business growth. Key Features for Project Management in Salesforce While Salesforce does not offer a dedicated project management solution, its native and customizable capabilities can effectively support project lifecycles: Using Salesforce for Project Management Maximize Salesforce’s capabilities for project management with these additional functionalities: Enhancing Project Management Explore third-party project management apps on the Salesforce AppExchange to further augment your project management capabilities. Options like Mission Control and Inspire Planner offer specialized features such as Gantt charts, resource planning, and collaboration tools, catering to diverse project management needs. While Salesforce provides robust features for project management, augmenting your solution with specialized apps can further enhance functionality and flexibility. By harnessing Salesforce’s capabilities, you can streamline project workflows, improve team collaboration, and ultimately deliver successful outcomes for your clients. If you require assistance or customization, certified project management professionals are available to support your endeavors. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 23, 2024in Salesforce
Einstein 1 Marketing and Commerce Tools
22May

Einstein 1 Marketing and Commerce Tools

Salesforce Unveils New Einstein 1 Marketing and Commerce Innovations to Enhance the Customer Journey with Unified Data and Trusted AI Einstein 1 Marketing and Commerce Tools announced at 2024 Connections event in Chicago, IL. Einstein Copilot for Marketers and Merchants: These tools enable brands to automatically generate campaign briefs, personalized content, and promotions using trusted data. Data Cloud for Commerce: Unifies business and customer data to deliver smart insights, allowing merchandisers to launch personalized promotions, offers, and shopping experiences, thus enhancing customer loyalty and boosting sales. Einstein Personalization: Uses the unified customer data profile in Data Cloud to automatically trigger the next best interaction based on customer behavior and history with a brand. Salesforce Expands Einstein Copilot Capabilities Today at Connections, Salesforce (NYSE: CRM), the leading AI CRM platform, announced new features for its Einstein Copilot. This trusted conversational AI assistant now aids marketers and merchants with daily tasks, in addition to its existing functionalities for sales and service. Salesforce also introduced new tools for unifying business and commerce data, along with an AI-powered personalization engine to enhance customer interactions at every touchpoint. “With the Einstein 1 Platform, we’re giving organizations the power to unify all their data on one trusted platform. This is key to achieving actionable AI-driven results.” Ariel Kelman, President and CMO of Salesforce Why It Matters Personalization is essential for customer satisfaction and business success. However, many organizations struggle to connect the right data and touchpoints to fully utilize AI for personalization. What’s New Einstein 1 Marketing and Commerce Tools Unified Data Platform: Brands can now unlock and unify all their data on a single platform, enabling personalized engagements across marketing, commerce, sales, and service. Key innovations include: Einstein Copilot for Marketers: Einstein Copilot for Merchants: Data Cloud for Commerce: Einstein Personalization: Unified AI Assistants Powered by Trusted Data Salesforce’s Einstein Copilot for Marketers and Merchants stand out due to their integration with the Einstein 1 Platform and Salesforce metadata. Unlike typical LLMs, Einstein Copilot uses metadata to interpret prompts with complete context, ensuring relevant and secure data usage. Einstein Trust Layer: Ensures the confidentiality of data within AI responses, maintaining security, privacy, and governance. Customer Perspective Matthew Randall, Head of Software and Integration at Aston Martin, praised Salesforce for enabling personalized, VIP experiences through unified data and AI capabilities. “The Einstein 1 Platform allows us to grow and enable our AI enterprise.” Availability Einstein 1 Marketing and Commerce Tools are evolving. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 22, 2024in Einstein 1 Platform
Salesforce Summer 24 Sales Release
22May

Salesforce Summer 24 Sales Release

Sales Salesforce Summer 24 Sales Release. Boost your sales teams’ results with new Einstein features, more actions, and improved performance and setup experiences. Sales rep’s get a boost to their productivity with standard and custom list view actions in the Account, Contact, and Lead Intelligence views. Sales teams have a bird’s-eye view of their conversations with customers with Conversation Signals. Sales managers have more flexibility in how they view forecasts. Enablement has an improved test and deploy experience for sales programs. And in Salesforce Maps, users experience better performance when plotting for high-volume data. Salesforce Summer 24 Sales Release Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 22, 2024in Salesforce
Salesforce and Google LLMs
22May

Salesforce and Google LLMs

In recent weeks, AI professionals had the privilege of attending groundbreaking hands-on workshops at the headquarters of two Silicon Valley giants, Salesforce and Google. These experiences offered a firsthand look at the contrasting approaches these tech titans are taking to bring enterprise-grade, large language model (LLM) applications to scale. As they immersed themselves in the cutting-edge world of AI development, a sense of excitement and awe washed over them at the unfolding history. Salesforce and Google LLMs. The workshops provided a fascinating glimpse into the future of enterprise software, where AI is not just a buzzword but a transformative force reshaping how businesses operate. Salesforce and Google, each with their unique strengths and philosophies, are at the forefront of this revolution, pushing the boundaries of what’s possible with LLMs and retrieval-augmented generation (RAG). As they navigated through the hands-on exercises and engaged with the brilliant minds behind these innovations, they realized they were witnessing a pivotal moment in Silicon Valley and computer history. Salesforce LLM Salesforce: Low-Code, Business User-Friendly At the “Build the Future with AI and Data Workshop” held at Salesforce Tower in downtown San Francisco, the focus was on empowering business users with a low-code, clicks-not-code approach. The workshop, attended by around 100 people, took place in a ballroom-sized auditorium. Each attendee received a free instance of the Generative AI-enabled org, pre-populated with a luxury travel destination application, which expired in 5 days. Data Cloud: Lots of Clicks The workshop began with setting up data ingestion and objects for linking AWS S3 buckets to Salesforce’s Data Cloud. The process was intricate, involving a new nomenclature reminiscent of SQL Views within Views, requiring a considerable number of setup steps before accessing Prompt Builder. It should be noted that when using Einstein Studio for the first time, users don’t normally need to do Data Cloud setup. This was done in this workshop so they could later include Data Cloud embeddings in a Prompt Builder retrieval. Prompt Builder: Easy to Use Prompt Builder was the highlight of the workshop. It allows for template variables and various prompt types, including the intriguing Field Prompt, which enables users to attach a prompt to a field. When editing a record, clicking the wizard button in that field executes the prompt, filling out the field automatically. This feature has the potential to greatly enhance data richness, with numerous use cases across industries. Integrating Flow and Apex with Prompt Builder demonstrated the platform’s flexibility. They created an Apex Class using Code Builder, which returned a list that could be used by Prompt Builder to formulate a reply. The seamless integration of these components showcased Salesforce’s commitment to providing a cohesive, user-friendly experience. Einstein Copilot, Salesforce’s AI assistant, exhibited out-of-the-box capabilities when integrated with custom actions. By creating a Flow and integrating it into a custom action, users could invoke Einstein Copilot to assist with various tasks. A Warmly Received Roadmap Salesforce managers, including SVP of Product Management John Kucera, provided insights into the Generative AI roadmap during a briefing session. They emphasized upcoming features such as Recommended Actions, which package prompts into buttons, and improved context understanding for Einstein Copilot. The atmosphere in the room was warm, with genuine excitement and a sense of collaboration between Salesforce staff and attendees. The workshop positioned Salesforce’s AI solution as an alternative to hiring an AI programmer and building AI orchestration using tools like those used in the Google workshop. Salesforce’s approach focuses on a user-friendly interface for setting up data sources and custom actions, enabling users to leverage AI without relying on code. This low-code philosophy aims to democratize AI, making it accessible to a broader range of business users. For organizations already invested in the Salesforce ecosystem, the platform’s embedded AI capabilities offer a compelling way to build expertise and leverage the power of Data Cloud. Salesforce’s commitment to rapidly rolling out embedded AI enhancements, all building on the familiar Admin user experience, makes it an attractive option for businesses seeking to adopt AI without the steep learning curve associated with coding. While there was palpable enthusiasm among attendees, the workshop also highlighted the complexity of setting up data sources and the challenges of working with a new nomenclature. As Salesforce continues to refine its AI offerings, striking the right balance between flexibility and ease of use will be crucial to widespread adoption. Google LLM Google: Engineering-Centric, Code-Intensive The “Build LLM-Powered Apps with Google” workshop, held on the Google campus in Mountain View, attracted around 150 attendees, primarily developers and engineers. They met in a large meeting room with circular tables. The event kicked off with a keynote presentation and detailed descriptions of Google’s efforts in creating retrieval-augmented generation (RAG) pipelines. They participated in a hands-on workshop, building a RAG database for an “SFO Assistant” chatbot designed to assist passengers at San Francisco airport. Running Postgres and pgvector with BigQuery Using Google Cloud Platform, they created a new VM running Postgres with the pgvector extension. They executed a series of commands to load the SFO database and establish a connection between Gemini and the database. The workshop provided step-by-step guidance, with Google staff helping when needed. Ultimately, they successfully ran a chatbot utilizing the RAG database. The workshop also showcased the power of BigQuery in generating prompts at scale through SQL statements. By crafting SQL queries that combined prompt engineering with retrieved data, they learned how to create personalized content, such as emails, for a group of customers in a single step. This demonstration highlighted the potential for efficient, large-scale content generation using Google’s tools. Gemini Assistant One of the most exciting discoveries for them during the workshop was the Gemini Assistant for BigQuery, a standout IT Companion Chatbot tailored for the GCP ecosystem. Comparable to GitHub Copilot Chat or ChatGPT-Plus, Gemini Assistant demonstrated a deep understanding of GCP and the ability to generate code snippets in various programming languages. What distinguishes Gemini Assistant is its strong grounding in GCP knowledge, enabling it to provide contextually

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May 22, 2024in Einstein 1 Platform, Generative AI, Salesforce
Summer 24 The AI Release
22May

Summer 24 Release Highlights for Admins

Release Readiness Essentials Summer 24 Release Highlights for Admins Video overview is here. Summer 24 Release Highlights for Admins Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 22, 2024in Salesforce
Salesforce Informatica Almost
22May

Salesforce Informatica Almost

The Deal That Never Was: Salesforce and Informatica In one of the biggest technology news stories of the year, it was reported in April that Salesforce was on the verge of acquiring cloud data management provider Informatica. Salesforce Informatica Almost. Both Bloomberg and The Wall Street Journal confirmed the story, with Bloomberg predicting that the deal could be finalized within days. Salesforce appeared poised to leverage Informatica’s data integration and management platform to enhance its Data Cloud and Einstein 1 solutions. However, by the following week, reports surfaced that the deal had fallen through due to an inability to agree on terms, with an unnamed Bloomberg source citing a disagreement over price. Neither company has disclosed specific reasons for the failed negotiations, but market reactions were notable, with both companies experiencing share price drops after the news broke. Salesforce has since somewhat recovered from its initial 7% decrease, but Informatica’s stock has continued to decline, now at its lowest point since mid-February. Criticism also emerged within the technology sector. Gaurav Dhillon, Co-Founder of Informatica and current CEO of SnapLogic, was particularly vocal, describing the proposed acquisition as a “real step backward” for Salesforce and expressing concerns about the merger’s impact on Informatica’s users. Dhillon predicted a “rocky road ahead” due to significant overlaps in integration products, specifically highlighting the challenge of merging Informatica’s technology with MuleSoft, an integration platform Salesforce acquired for $6.5 billion in 2018. Dhillon warned that integrating these disparate platforms would be a complex, time-consuming project likely to take more than five years to complete. Industry Analysts Weigh In The topic was recently revisited by leading CX analysts during a CX Today Big CX News discussion. Despite the initial market and industry criticism, many analysts agreed that the acquisition made strategic sense for Salesforce. Martin Schneider, Head of Research at Annuitas Research, emphasized that data quality is a longstanding issue in the CRM sector and described Informatica’s data capabilities as the missing “puzzle piece” for Salesforce’s end-to-end, AI-driven strategy. He stated, “One thing that Informatica does incredibly well is data quality. Having a CDP is one thing, but unless you actually have the data set right, you can’t create a free-flowing customer data value chain.” Michael Fauscette, Founder, CEO & Chief Analyst at Arion Research, echoed this sentiment, highlighting the enhancements Informatica could have brought to the backend of Data Cloud as a missed opportunity. “If you think about what Salesforce has done over the last couple of years with Data Cloud, it really completes that story from the backend,” he said. “The part of how do I get the data prep and make sure the quality is there.” While acknowledging that the price may have been a sticking point, particularly given the overlap with Salesforce’s existing solutions, Zeus Kerravala, Principal Analyst at ZK Research, expressed surprise that Salesforce walked away from the deal. He asserted, “If an acquisition is a good acquisition, you can never pay too much for it.” Kerravala further explained that data quality issues are a significant hindrance to Salesforce’s AI capabilities. “Salesforce customers are notorious for putting bad data into Salesforce, and bad data leads to bad output. If there’s one thing they needed, it was a company like Informatica to help with that.” Conclusion Despite the week-long will-they-won’t-they drama, the potential acquisition of Informatica by Salesforce remains a ‘what if.’ While initial market reactions and industry criticisms suggested that the failed deal might have been for the best, many CX analysts believe it represented a missed opportunity for Salesforce to enhance its data management and AI capabilities. As the dust settles, the implications of this near-acquisition will continue to be a topic of discussion in the CX community. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 22, 2024in Mulesoft, Salesforce
Education Cloud Academic Operations Explained
21May

Education Cloud Academic Operations Explained

Education Cloud Academic Operations Academic Operations serves as the central hub for creating and managing your institution’s learning-related objects and the relationships between them. With this powerful tool, staff can: The entities you set up in Academic Operations—such as learning courses, programs, and schedules—lay the groundwork for the Recruitment & Admissions and Student Success apps. For instance, curricula and program data form the basis of your course catalog, while plans created in Program Plan Builder flow into Intelligent Degree Planning, guiding the Learner Progress View. Configuring Academic Operations To configure Academic Operations for your institution: Integration Capabilities Salesforce’s education data model seamlessly integrates with various Salesforce tools, including Data Cloud, Marketing Cloud, Salesforce Scheduler, and Einstein AI, as well as custom components like a comments feature and outcome management tools. This integration ensures a comprehensive solution for managing and enhancing the entire learning experience. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 21, 2024in Salesforce Education Cloud, Salesforce Education Solutions
AMPScript Editor Explained
21May

AMPScript Editor Explained

What is the Purpose of AMPscript? AMPScript Editor Explained. AMPscript serves a multitude of purposes, primarily focusing on personalization within Salesforce Marketing Cloud. This scripting language empowers users to personalize their emails by integrating subscriber or contact data. From addressing recipients by their first names to tailoring content based on individual preferences, AMPscript enhances the overall effectiveness of marketing campaigns. Exploring Inline AMPscript Inline AMPscript represents a specific use of AMPscript, distinguishing itself from AMPscript blocks. While AMPscript blocks can contain multiple lines of code, inline AMPscript typically serves a single function. The output of this function appears at the code’s location within the message. Noteworthy, inline AMPscript supports nested functions, contributing to its versatility. Understanding AMPscript in Salesforce Marketing Cloud AMPscript is Salesforce Marketing Cloud’s proprietary scripting language, prized for its ease of learning and its capacity to facilitate personalization across diverse digital marketing channels. It seamlessly integrates within HTML emails, text emails, landing pages, SMS messages, or push notifications. However, Salesforce Marketing Cloud lacks dedicated tools for editing AMPscript, both within and outside the user interface, resulting in a somewhat rudimentary and error-prone script-writing experience. Enhancing the AMPscript Editing Experience To improve the AMPscript editing process, various tools and extensions have been developed: Retrieving Data with AMPscript To fetch data from a data extension using AMPscript, the Lookup() function is employed. This function necessitates parameters such as the data extension name, the column for data retrieval, and the columns utilized for search and value specification. Like1 Related Posts Salesforce Data Studio Data Studio Overview Salesforce Data Studio is Salesforce’s premier solution for audience discovery, data acquisition, and data provisioning, offering access Read more How Travel Companies Are Using Big Data and Analytics In today’s hyper-competitive business world, travel and hospitality consumers have more choices than ever before. With hundreds of hotel chains Read more Integration of Salesforce Sales Cloud to Google Analytics 360 Announced In November 2017, Google unveiled a groundbreaking partnership with Salesforce, outlining their commitment to develop innovative integrations between Google Analytics Read more Overlooked Costs of a Salesforce Implementation Let’s look at some frequently overlooked Salesforce costs. The goal is to provide businesses and decision-makers with a comprehensive understanding Read more

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May 21, 2024in Salesforce Marketing Cloud
Connections and State of AI
21May

Connections and State of AI

Salesforce Unveils Latest State of Marketing Study Ahead of Annual Connections Conference CHICAGO, May 21, 2024 – As Salesforce gears up for its annual Connections marketing and commerce conference, the company has released the ninth edition of its State of Marketing study. This year’s conference, themed around AI, marketing, and commerce, sets the stage for a deep dive into the future of these interconnected fields. AI Takes Center Stage: The study, drawing insights from over 4,800 marketers across 29 countries, reveals that AI is both the top implementation priority and the biggest challenge for marketers in the coming year. An impressive 63% of marketers currently use generative AI, with an additional 35% planning to adopt the technology within the next 18 months. Key AI applications identified include automating customer interactions, generating content, analyzing performance, automating data integration, and driving real-time best offers. Regional Variations: While AI is a global priority, regional differences are notable. In the US, AI implementation ranks second to improving ROI/attribution, whereas in the UK, it doesn’t even make the top five priorities. Despite these differences, both US and UK marketers cite AI implementation as their third greatest challenge. Countries prioritizing AI include South Korea, UAE, Argentina, Germany, Italy, Japan, Poland, Portugal, and Spain. Interestingly, AI does not feature in the top five priorities for India and Singapore. Challenges in AI Implementation: Across the board, data exposure and leakage are the top concerns related to generative AI, followed by a lack of necessary data, unclear strategy or use cases, fear of inaccurate outputs, and concerns about copyright/IP issues. These challenges vary by industry. For instance, government and media/entertainment sectors worry about AI job displacement, while other sectors focus on biases, brand adherence, and general distrust of AI. Data Integration Struggles: Marketers use an average of nine different tactics to capture customer data, including customer service interactions (88%), transaction data (82%), mobile apps (82%), web registrations (82%), and loyalty programs (80%). However, integrating this data into a unified system remains a significant challenge. Only 31% of marketers are fully satisfied with their ability to unify customer data, and many still rely on IT support for basic marketing tasks. The Personalization Paradox: Despite technological advances, fewer than six in 10 marketers can fully personalize familiar channels like email and mobile messaging. This gap highlights the ongoing struggle to meet rising customer expectations for personalized experiences. Steve Hammond, EVP and GM of Marketing Cloud at Salesforce, emphasizes the importance of personalization at scale: “Customers want to feel like they’re more than just a number. They want relevant experiences that create relationships. But personalization is still a challenge, especially at massive scale.” Looking Ahead: The findings from the State of Marketing study will undoubtedly fuel discussions at Connections. While the potential of AI is exciting, the need for a solid data foundation is critical for realizing its benefits. As the conference unfolds, diginomica’s Jon Reed will be on the ground in Chicago, providing updates on key insights and discussions. About Salesforce: Salesforce is the leading AI CRM, empowering companies to connect with their customers through a unified platform that combines CRM, AI, data, and trust. For more information, visit www.salesforce.com. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 21, 2024in Salesforce, Salesforce Einstein
TEFCA could drive payer-provider interoperability
20May

TEFCA could drive payer-provider interoperability

Bridging the Interoperability Gap: TEFCA’s Role in Payer-Provider Data Exchange The electronic health information exchange (HIE) between healthcare providers has seen significant growth in recent years. However, interoperability between healthcare providers and payers has lagged behind. The Trusted Exchange Framework and Common Agreement (TEFCA) aims to address this gap and enhance data interoperability across the healthcare ecosystem. TEFCA could drive payer-provider interoperability with a little help from the world of technology. TEFCA’s Foundation and Evolution TEFCA was established under the 21st Century Cures Act to improve health data interoperability through a “network of networks” approach. The Office of the National Coordinator for Health Information Technology (ONC) officially launched TEFCA in December 2023, designating five initial Qualified Health Information Networks (QHINs). By February 2024, two additional QHINs had been designated. The Sequoia Project, TEFCA’s recognized coordinating entity, recently released several key documents for stakeholder feedback, including draft standard operating procedures (SOPs) for healthcare operations and payment under TEFCA. During the 2024 WEDI Spring Conference, leaders from three QHINs—eHealth Exchange, Epic Nexus, and Kno2—discussed the future of TEFCA in enhancing provider and payer interoperability. ONC released Version 2.0 of the Common Agreement on April 22, 2024. Common Agreement Version 2.0 updates Common Agreement Version 1.1, published in November 2023, and includes enhancements and updates to require support for Health Level Seven (HL7®) Fast Healthcare Interoperability Resources (FHIR®) based transactions. The Common Agreement includes an exhibit, the Participant and Subparticipant Terms of Participation (ToP), that sets forth the requirements each Participant and Subparticipant must agree to and comply with to participate in TEFCA. The Common Agreement and ToPs incorporate all applicable standard operating procedures (SOPs) and the Qualified Health Information Network Technical Framework (QTF). View the release notes for Common Agreement Version 2.0 The Trusted Exchange Framework and Common AgreementTM (TEFCATM) has 3 goals: (1) to establish a universal governance, policy, and technical floor for nationwide interoperability; (2) to simplify connectivity for organizations to securely exchange information to improve patient care, enhance the welfare of populations, and generate health care value; and (3) to enable individuals to gather their health care information. Challenges in Payer Data Exchange Although the QHINs on the panel have made progress in facilitating payer HIE, they emphasized that TEFCA is not yet fully operational for large-scale payer data exchange. Ryan Bohochik, Vice President of Value-Based Care at Epic, highlighted the complexities of payer-provider data exchange. “We’ve focused on use cases that allow for real-time information sharing between care providers and insurance carriers,” Bohochik said. “However, TEFCA isn’t yet capable of supporting this at the scale required.” Bohochik also pointed out that payer data exchange is complicated by the involvement of third-party contractors. For example, health plans often partner with vendors for tasks like care management or quality measure calculation. This adds layers of complexity to the data exchange process. Catherine Bingman, Vice President of Interoperability Adoption for eHealth Exchange, echoed these concerns, noting that member attribution and patient privacy are critical issues in payer data exchange. “Payers don’t have the right to access everything a patient has paid for themselves,” Bingman said. “This makes providers cautious about sharing data, impacting patient care.” For instance, manual prior authorization processes frequently delay patient access to care. A 2023 AMA survey found that 42% of doctors reported care delays due to prior authorization, with 37% stating that these delays were common. Building Trust Through Use Cases Matt Becker, Vice President of Interoperability at Kno2, stressed the importance of developing specific use cases to establish trust in payer data exchange via TEFCA. “Payment and operations is a broad category that includes HEDIS measures, quality assurance, and provider monitoring,” Becker said. “Each of these requires a high level of trust.” Bohochik agreed, emphasizing that narrowing the scope and focusing on specific, high-value use cases will be essential for TEFCA’s adoption. “We can’t solve everything at once,” Bohochik said. “We need to focus on achieving successful outcomes in targeted areas, which will build momentum and community support.” He also noted that while technical data standards are crucial, building trust in the data exchange process is equally important. “A network is only as good as the trust it inspires,” Bohochik said. “If healthcare systems know that data requests for payment and operations are legitimate and secure, it will drive the scalability of TEFCA.” By focusing on targeted use cases, ensuring rigorous data standards, and building trust, TEFCA has the potential to significantly enhance interoperability between healthcare providers and payers, ultimately improving patient care and operational efficiency. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 20, 2024in Salesforce Health and Life Sciences Solutions

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